Search results for: pin fin heat sink optimization

Authors: Panagiotis Gkekas, Christos Sougles, Dionysios Kehagias, Dimitrios Tzovaras

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This paper presents the architecture of the “Intelligent cooperative integrated system for road safety and road infrastructure maintenance towards 2020” (ODOS2020) advanced infrastructure, which implements a number of cooperative ITS applications based on Internet of Things and Infrastructure-to-Vehicle (V2I) technologies with the purpose to enhance the active road safety level of vehicles through the provision of a fully automated V2I environment. The primary objective of the ODOS2020 project is to contribute to increased road safety but also to the optimization of time for maintenance of road infrastructure. The integrated technological solution presented in this paper addresses all types of vehicles and requires minimum vehicle equipment. Thus, the ODOS2020 comprises a low-cost solution, which is one of its main benefits. The system architecture includes an integrated notification system to transmit personalized information on road, traffic, and environmental conditions, in order for the drivers to receive real-time and reliable alerts concerning upcoming critical situations. The latter include potential dangers on the road, such as obstacles or road works ahead, extreme environmental conditions, etc., but also informative messages, such as information on upcoming tolls and their charging policies. At the core of the system architecture lies an integrated sensorial network embedded in special road infrastructures (strips) that constantly collect and transmit wirelessly information about passing vehicles’ identification, type, speed, moving direction and other traffic information in combination with environmental conditions and road wear monitoring and predictive maintenance data. Data collected from sensors is transmitted by roadside infrastructure, which supports a variety of communication technologies such as ITS-G5 (IEEE-802.11p) wireless network and Internet connectivity through cellular networks (3G, LTE). All information could be forwarded to both vehicles and Traffic Management Centers (TMC) operators, either directly through the ITS-G5 network, or to smart devices with Internet connectivity, through cloud-based services. Therefore, through its functionality, the system could send personalized notifications/information/warnings and recommendations for upcoming events to both road users and TMC operators. In the course of the ODOS2020 project pilot operation has been conducted to allow drivers of both C-ITS equipped and non-equipped vehicles to experience the provided added value services. For non-equipped vehicles, the provided information is transmitted to a smartphone application. Finally, the ODOS2020 system and infrastructure is appropriate for installation on both urban, rural, and highway environments. The paper presents the various parts of the system architecture and concludes by outlining the various challenges that had to be overcome during its design, development, and deployment in a real operational environment. Acknowledgments: Work presented in this paper was co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation (call RESEARCH–CREATE–INNOVATE) under contract no. Τ1EDK-03081 (project ODOS2020).

Keywords: infrastructure to vehicle, intelligent transportation systems, internet of things, road safety

Procedia PDF Downloads 86

Authors: Priyanka Yadav, Umesh Bnasal, Yashvinder Kumar

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The placenta is an important structure that provides oxygen and nutrients to the growing fetus in utero. It is usually thrown away after birth, but it has a therapeutic role in the regeneration of tissue. It is covered by the amniotic membrane, which can be easily separated into the amnion layer and the chorion layer—the amnion layer act as a biofilm for the healing of burn wound and non-healing ulcers. The freshly collected membrane has stem cells, cytokines, growth factors, and anti-inflammatory properties, which act as a biofilm for the healing of wounds. It functions as a barrier and prevents heat and water loss and also protects from bacterial contamination, thus supporting the healing process. The application of Amnion membranes has been successfully used for wound and reconstructive purposes for decades. It is a very cheap and easy process and has shown superior results to allograft and xenograft. However, there are very few case reports of amnion membrane grafting in newborns; we intend to highlight its therapeutic importance in burn injuries in newborns. We present a case of 9 days old male neonate who presented to the neonatal unit of Maulana Azad Medical College with a complaint of fluid-filled blisters and burns wound on the body for six days. He was born outside the hospital at 38 weeks of gestation to a 24-year-old primigravida mother by vaginal delivery. The presentation was cephalic and the amniotic fluid was clear. His birth weight was 2800 gm and APGAR scores were 7 and 8 at 1 and 5 minutes, respectively. His anthropometry was appropriate for gestational age. He developed respiratory distress after birth requiring oxygen support by nasal prongs for three days. On the day of life three, he developed blisters on his body, starting from than face then over the back and perineal region. At a presentation on the day of life nine, he had blisters and necrotic wound on the right side of the face, back, right shoulder and genitalia, affecting 60% of body surface area with full-thickness loss of skin. He was started on intravenous antibiotics and fluid therapy. Pus culture grew Pseudomonas aeuroginosa, for which culture-specific antibiotics were started. Plastic surgery reference was taken and regular wound dressing was done with antiseptics. He had a storming course during the hospital stay. On the day of life 35 when the baby was hemodynamically stable, amnion membrane grafting was done on the wound site; for the grafting, fresh amnion membrane was removed under sterile conditions from the placenta obtained by caesarean section. It was then transported to the plastic surgery unit in half an hour in a sterile fluid where the graft was applied over the infant’s wound. The amnion membrane grafting was done twice in two weeks for covering the whole wound area. After successful uptake of amnion membrane, skin from the thigh region was autografted over the whole wound area by Meek technique in a single setting. The uptake of autograft was excellent and most of the areas were healed. In some areas, there was patchy regeneration of skin so dressing was continued. The infant was discharged after three months of hospital stay and was later followed up in the plastic surgery unit of the hospital.

Keywords: amnion membrane grafting, autograft, meek technique, newborn, regeneration of skin

Procedia PDF Downloads 143

Authors: Sanaz Moayer, Fang Huang, Scott Gardner

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In the highly leveraged business world of today, an organisation’s success depends on how it can manage and organize its traditional and intangible assets. In the knowledge-based economy, knowledge as a valuable asset gives enduring capability to firms competing in rapidly shifting global markets. It can be argued that ability to create unique knowledge assets by configuring ICT and human capabilities, will be a defining factor for international competitive advantage in the mid-21st century. The concept of KM is recognized in the strategy literature, and increasingly by senior decision-makers (particularly in large firms which can achieve scalable benefits), as an important vehicle for stimulating innovation and organisational performance in the knowledge economy. This thinking has been evident in professional services and other knowledge intensive industries for over a decade. It highlights the importance of social capital and the value of the intellectual capital embedded in social and professional networks, complementing the traditional focus on creation of intellectual property assets. Despite the growing interest in KM within professional services there has been limited discussion in relation to multinational resource based industries such as mining and petroleum where the focus has been principally on global portfolio optimization with economies of scale, process efficiencies and cost reduction. The Australian minerals and metals mining industry, although traditionally viewed as capital intensive, employs a significant number of knowledge workers notably- engineers, geologists, highly skilled technicians, legal, finance, accounting, ICT and contracts specialists working in projects or functions, representing potential knowledge silos within the organisation. This silo effect arguably inhibits knowledge sharing and retention by disaggregating corporate memory, with increased operational and project continuity risk. It also may limit the potential for process, product, and service innovation. In this paper the strategic application of knowledge management incorporating contemporary ICT platforms and data mining practices is explored as an important enabler for knowledge discovery, reduction of risk, and retention of corporate knowledge in resource based industries. With reference to the relevant strategy, management, and information systems literature, this paper highlights possible connections (currently undergoing empirical testing), between an Strategic Knowledge Management (SKM) framework incorporating supportive Data Mining (DM) practices and competitive advantage for multinational firms operating within the Australian resource sector. We also propose based on a review of the relevant literature that more effective management of soft and hard systems knowledge is crucial for major Australian firms in all sectors seeking to improve organisational performance through the human and technological capability captured in organisational networks.

Keywords: competitive advantage, data mining, mining organisation, strategic knowledge management

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Authors: Chen Jiang, Eric Jordan, Maurice Gell, Balakrishnan Nair

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Nuclear fusion, one of the most promising options for reliably generating large amounts of carbon-free energy in the future, has seen a plethora of ground-breaking technological advances in recent years. An efficient and durable “breeding blanket”, needed to ensure a reactor’s self-sufficiency by maintaining the optimal coolant temperature as well as by minimizing radiation dosage behind the blanket, still remains a technological challenge for the various reactor designs for commercial fusion power plants. A relatively new dual-coolant lead-lithium (DCLL) breeder design has exhibited great potential for high-temperature (>700oC), high-thermal-efficiency (>40%) fusion reactor operation. However, the structural material, namely reduced activation ferritic-martensitic (RAFM) steel, is not chemically stable in contact with molten Pb-17%Li coolant. Thus, to utilize this new promising reactor design, the demand for effective corrosion-resistant coatings on RAFM steels represents a pressing need. Solution Spray Technologies LLC (SST) is developing a double-layer ceramic coating design to address the corrosion protection of RAFM steels, using a novel solution and solution/suspension plasma spray technology through a US Department of Energy-funded project. Plasma spray is a coating deposition method widely used in many energy applications. Novel derivatives of the conventional powder plasma spray process, known as the solution-precursor and solution/suspension-hybrid plasma spray process, are powerful methods to fabricate thin, dense ceramic coatings with complex compositions necessary for the corrosion protection in DCLL breeders. These processes can be used to produce ultra-fine molten splats and to allow fine adjustment of coating chemistry. Thin, dense ceramic coatings with chosen chemistry for superior chemical stability in molten Pb-Li, low activation properties, and good radiation tolerance, is ideal for corrosion-protection of RAFM steels. A key challenge is to accommodate its CTE mismatch with the RAFM substrate through the selection and incorporation of appropriate bond layers, thus allowing for enhanced coating durability and robustness. Systematic process optimization is being used to define the optimal plasma spray conditions for both the topcoat and bond-layer, and X-ray diffraction and SEM-EDS are applied to successfully validate the chemistry and phase composition of the coatings. The plasma-sprayed double-layer corrosion resistant coatings were also deposited onto simulated RAFM steel substrates, which are being tested separately under thermal cycling, high-temperature moist air oxidation as well as molten Pb-Li capsule corrosion conditions. Results from this testing on coated samples, and comparisons with bare RAFM reference samples will be presented and conclusions will be presented assessing the viability of the new ceramic coatings to be viable corrosion prevention systems for DCLL breeders in commercial nuclear fusion reactors.

Keywords: breeding blanket, corrosion protection, coating, plasma spray

Procedia PDF Downloads 283

Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

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Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

Procedia PDF Downloads 139

Authors: Alexander A. Stakheev, Larisa V. Samokhvalova, Sergey K. Zavriev

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Fusarium fungi are among the most devastating plant pathogens distributed all over the world. Significant reduction of grain yield and quality caused by Fusarium leads to multi-billion dollar annual losses to the world agricultural production. These organisms can also cause infections in immunocompromised persons and produce the wide range of mycotoxins, such as trichothecenes, fumonisins, and zearalenone, which are hazardous to human and animal health. Identification of Fusarium fungi based on the morphology of spores and spore-forming structures, colony color and appearance on specific culture media is often very complicated due to the high similarity of these features for closely related species. Modern Fusarium taxonomy increasingly uses data of crossing experiments (biological species concept) and genetic polymorphism analysis (phylogenetic species concept). A number of novel Fusarium sibling species has been established using DNA barcoding techniques. Species recognition is best made with the combined phylogeny of intron-rich protein coding genes and ribosomal DNA sequences. However, the internal transcribed spacer of (ITS), which is considered to be universal DNA barcode for Fungi, is not suitable for genus Fusarium, because of its insufficient variability between closely related species and the presence of non-orthologous copies in the genome. Nowadays, the translation elongation factor 1 alpha (TEF1α) gene is the “gold standard” of Fusarium taxonomy, but the search for novel informative markers is still needed. In this study, we used two novel DNA markers, frataxin (FXN) and heat shock protein 90 (HSP90) to discover phylogenetic relationships between Fusarium species. Multilocus phylogenetic analysis based on partial sequences of TEF1α, FXN, HSP90, as well as intergenic spacer of ribosomal DNA (IGS), beta-tubulin (β-TUB) and phosphate permease (PHO) genes has been conducted for 120 isolates of 19 Fusarium species from different climatic zones of Russia and neighboring countries using maximum likelihood (ML) and maximum parsimony (MP) algorithms. Our analyses revealed that FXN and HSP90 genes could be considered as informative phylogenetic markers, suitable for evolutionary and taxonomic studies of Fusarium genus. It has been shown that PHO gene possesses more variable (22 %) and parsimony informative (19 %) characters than other markers, including TEF1α (12 % and 9 %, correspondingly) when used for elucidating phylogenetic relationships between F. avenaceum and its closest relatives – F. tricinctum, F. acuminatum, F. torulosum. Application of novel DNA barcodes confirmed the fact that F. arthrosporioides do not represent a separate species but only a subspecies of F. avenaceum. Phylogeny based on partial PHO and FXN sequences revealed the presence of separate cluster of four F. avenaceum strains which were closer to F. torulosum than to major F. avenaceum clade. The strain F-846 from Moldova, morphologically identified as F. poae, formed a separate lineage in all the constructed dendrograms, and could potentially be considered as a separate species, but more information is needed to confirm this conclusion. Variable sites in PHO sequences were used for the first-time development of specific qPCR-based diagnostic assays for F. acuminatum and F. torulosum. This work was supported by Russian Foundation for Basic Research (grant № 15-29-02527).

Keywords: DNA barcode, fusarium, identification, phylogenetics, taxonomy

Procedia PDF Downloads 295

Authors: J. Ticona Chambi, E. A. De Almeida, C. A. Andrade Raymundo Gaiotto, A. M. Do Espírito Santo, L. Infantes, S. L. Cuffini

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The solubility of active pharmaceutical ingredients (APIs) is challenging for the pharmaceutical industry. The new multicomponent crystalline forms as cocrystal and solvates present an opportunity to improve the solubility of APIs. Commonly, the procedure to obtain multicomponent crystalline forms of a drug starts by screening the drug molecule with the different coformers/solvents. However, it is necessary to develop methods to obtain multicomponent forms in an efficient way and with the least possible environmental impact. The Hansen Solubility Parameters (HSPs) is considered a tool to obtain theoretical knowledge of the solubility of the target compound in the chosen solvent. H-Bond Propensity (HBP), Molecular Complementarity (MC), Coordination Values (CV) are tools used for statistical prediction of cocrystals developed by the Cambridge Crystallographic Data Center (CCDC). The HSPs and the CCDC tools are based on inter- and intra-molecular interactions. The curcumin (Cur), target molecule, is commonly used as an anti‐inflammatory. The demethoxycurcumin (Demcur) and bisdemethoxycurcumin (Bisdcur) are natural analogues of Cur from turmeric. Those target molecules have differences in their solubilities. In this way, the work aimed to analyze and compare different tools for multicomponent forms prediction (solvates) of Cur, Demcur and Biscur. The HSP values were calculated for Cur, Demcur, and Biscur using the chemical group contribution methods and the statistical optimization from experimental data. The HSPmol software was used. From the HSPs of the target molecules and fifty solvents (listed in the HSP books), the relative energy difference (RED) was determined. The probability of the target molecules would be interacting with the solvent molecule was determined using the CCDC tools. A dataset of fifty molecules of different organic solvents was ranked for each prediction method and by a consensus ranking of different combinations: HSP, CV, HBP and MC values. Based on the prediction, 15 solvents were selected as Dimethyl Sulfoxide (DMSO), Tetrahydrofuran (THF), Acetonitrile (ACN), 1,4-Dioxane (DOX) and others. In a starting analysis, the slow evaporation technique from 50°C at room temperature and 4°C was used to obtain solvates. The single crystals were collected by using a Bruker D8 Venture diffractometer, detector Photon100. The data processing and crystal structure determination were performed using APEX3 and Olex2-1.5 software. According to the results, the HSPs (theoretical and optimized) and the Hansen solubility sphere for Cur, Demcur and Biscur were obtained. With respect to prediction analyses, a way to evaluate the predicting method was through the ranking and the consensus ranking position of solvates already reported in the literature. It was observed that the combination of HSP-CV obtained the best results when compared to the other methods. Furthermore, as a result of solvent selected, six new solvates, Cur-DOX, Cur-DMSO, Bicur-DOX, Bircur-THF, Demcur-DOX, Demcur-ACN and a new Biscur hydrate, were obtained. Crystal structures were determined for Cur-DOX, Biscur-DOX, Demcur-DOX and Bicur-Water. Moreover, the unit-cell parameter information for Cur-DMSO, Biscur-THF and Demcur-ACN were obtained. The preliminary results showed that the prediction method is showing a promising strategy to evaluate the possibility of forming multicomponent. It is currently working on obtaining multicomponent single crystals.

Keywords: curcumin, HSPs, prediction, solvates, solubility

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Authors: E. Locatelli, I. Monaco, R. C. Martin, Y. Li, R. Pini, M. Chiariello, M. Comes Franchini

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Despite the many advantages of application of nanomaterials in the field of nanomedicine, increasing concerns have been expressed on their potential adverse effects on human health. There is urgency for novel green strategies toward novel materials with enhanced biocompatibility using safe reagents. Photothermal ablation therapy, which exploits localized heat increase of a few degrees to kill cancer cells, has appeared recently as a non-invasive and highly efficient therapy against various cancer types; anyway new agents able to generate hyperthermia when irradiated are needed and must have precise biocompatibility in order to avoid damage to healthy tissues and prevent toxicity. Recently, there has been increasing interest in magnesium as a biomaterial: it is the fourth most abundant cation in the human body, and it is essential for human metabolism. However magnesium nanoparticles (Mg NPs) have had limited diffusion due to the high reduction potential of magnesium cations, which makes NPs synthesis challenging. Herein, we report the synthesis of Mg NPs and their surface functionalization for the obtainment of a stable and biocompatible nanomaterial suitable for photothermal ablation therapy against cancer. We synthesized the Mg crystals by reducing MgCl2 with metallic lithium and exploiting naphthalene as an electron carrier: the lithium–naphthalene complex acts as the real reducing agent. Firstly, the nanocrystal particles were coated with the ligand 12-ethoxy ester dodecanehydroxamic acid, and then entrapped into water-dispersible polymeric micelles (PMs) made of the FDA-approved PLGA-b-PEG-COOH copolymer using the oil-in-water emulsion technique. Lately, we developed a more straightforward methodology by introducing chitosan, a highly biocompatible natural product, at the beginning of the process, simultaneously using lithium–naphthalene complex, thus having a one-pot procedure for the formation and surface modification of MgNPs. The obtained MgNPs were purified and fully characterized, showing diameters in the range of 50-300 nm. Notably, when coated with chitosan the particles remained stable as dry powder for more than 10 months. We proved the possibility of generating a temperature rise of a few to several degrees once MgNPs were illuminated using a 810 nm diode laser operating in continuous wave mode: the temperature rise resulted significant (0-15 °C) and concentration dependent. We then investigated potential cytotoxicity of the MgNPs: we used HN13 epithelial cells, derived from a head and neck squamous cell carcinoma and the hepa1-6 cell line, derived from hepatocellular carcinoma and very low toxicity was observed for both nanosystems. Finally, in vivo photothermal therapy was performed on xenograft hepa1-6 tumor bearing mice: the animals were treated with MgNPs coated with chitosan and showed no sign of suffering after the injection. After 12 hours the tumor was exposed to near-infrared laser light. The results clearly showed an extensive damage to tumor tissue after only 2 minutes of laser irradiation at 3Wcm-1, while no damage was reported when the tumor was treated with the laser and saline alone in control group. Despite the lower photothermal efficiency of Mg with respect to Au NPs, we consider MgNPs a promising, safe and green candidate for future clinical translations.

Keywords: chitosan, magnesium nanoparticles, nanomedicine, photothermal therapy

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Authors: Mohammadreza Nematollahi, Bahareh Mosadegh Sedghy, Alireza Tajbakhsh

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The last two decades have witnessed substantial attention to organic and sustainable agricultural supply chains. Motivated by real-world practices, this paper aims to address two main challenges observed in organic product supply chains: decentralized decision-making process between farmers and their retailers, and competition between organic products and their conventional counterparts. To this aim, an agricultural supply chain consisting of two farmers, a conventional farmer and an organic farmer who offers an organic version of the same product, is considered. Both farmers distribute their products through a single retailer, where there exists competition between the organic and the conventional product. The retailer, as the market leader, sets the wholesale price, and afterward, the farmers set their production quantity decisions. This paper first models the demand functions of the conventional and organic products by incorporating the effect of asymmetric brand equity, which captures the fact that consumers usually pay a premium for organic due to positive perceptions regarding their health and environmental benefits. Then, profit functions with consideration of some characteristics of organic farming, including crop yield gap and organic cost factor, are modeled. Our research also considers both economies and diseconomies of scale in farming production as well as the effects of organic subsidy paid by the government to support organic farming. This paper explores the investigated supply chain in three scenarios: decentralized, centralized, and coordinated decision-making structures. In the decentralized scenario, the conventional and organic farmers and the retailer maximize their own profits individually. In this case, the interaction between the farmers is modeled under the Bertrand competition, while analyzing the interaction between the retailer and farmers under the Stackelberg game structure. In the centralized model, the optimal production strategies are obtained from the entire supply chain perspective. Analytical models are developed to derive closed-form optimal solutions. Moreover, analytical sensitivity analyses are conducted to explore the effects of main parameters like the crop yield gap, organic cost factor, organic subsidy, and percent price premium of the organic product on the farmers’ and retailer’s optimal strategies. Afterward, a coordination scenario is proposed to convince the three supply chain members to shift from the decentralized to centralized decision-making structure. The results indicate that the proposed coordination scenario provides a win-win-win situation for all three members compared to the decentralized model. Moreover, our paper demonstrates that the coordinated model respectively increases and decreases the production and price of organic produce, which in turn motivates the consumption of organic products in the market. Moreover, the proposed coordination model helps the organic farmer better handle the challenges of organic farming, including the additional cost and crop yield gap. Last but not least, our results highlight the active role of the organic subsidy paid by the government as a means of promoting sustainable organic product supply chains. Our paper shows that although the amount of organic subsidy plays a significant role in the production and sales price of organic products, the allocation method of subsidy between the organic farmer and retailer is not of that importance.

Keywords: analytical game-theoretic model, product competition, supply chain coordination, sustainable organic supply chain

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Authors: Piotr Wadolowski, Grzegorz Krzesinski, Piotr Gutowski

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The aim of the presented investigation is to recognize the possible mechanical issues of mini-plate connection used to treat mandible fractures and to check the impact of different factors for the stresses and displacements within the bone-stabilizer system. The mini-plate osteosynthesis technique is a common type of internal fixation using metal plates connected to the fractured bone parts by a set of screws. The selected two types of plate application methodology used by maxillofacial surgeons were investigated in the work. Those patterns differ in location and number of plates. The bone geometry was modeled on the base of computed tomography scans of hospitalized patient done just after mini-plate application. The solid volume geometry consisting of cortical and cancellous bone was created based on gained cloud of points. Temporomandibular joint and muscle system were simulated to imitate the real masticatory system behavior. Finite elements mesh and analysis were performed by ANSYS software. To simulate realistic connection behavior nonlinear contact conditions were used between the connecting elements and bones. The influence of the initial compression of the connected bone parts or the gap between them was analyzed. Nonlinear material properties of the bone tissues and elastic-plastic model of titanium alloy were used. The three cases of loading assuming the force of magnitude of 100N acting on the left molars, the right molars and the incisors were investigated. Stress distribution within connecting plate shows that the compression of the bone parts in the connection results in high stress concentration in the plate and the screws, however the maximum stress levels do not exceed material (titanium) yield limit. There are no significant differences between negative offset (gap) and no-offset conditions. The location of the external force influences the magnitude of stresses around both the plate and bone parts. Two-plate system gives generally lower von Misses stress under the same loading than the one-plating approach. Von Mises stress distribution within the cortical bone shows reduction of high stress field for the cases without the compression (neutral initial contact). For the initial prestressing there is a visible significant stress increase around the fixing holes at the bottom mini-plate due to the assembly stress. The local stress concentration may be the reason of bone destruction in those regions. The performed calculations prove that the bone-mini-plate system is able to properly stabilize the fractured mandible bone. There is visible strong dependency between the mini-plate location and stress distribution within the stabilizer structure and the surrounding bone tissue. The results (stresses within the bone tissues and within the devices, relative displacements of the bone parts at the interface) corresponding to different models of the connection provide a basis for the mechanical optimization of the mini-plate connections. The results of the performed numerical simulations were compared to clinical observation. They provide information helpful for better understanding of the load transfer in the mandible with the stabilizer and for improving stabilization techniques.

Keywords: finite element modeling, mandible fracture, mini-plate connection, osteosynthesis

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Authors: K. Ghosh, S. N. Tripathi, Manish Joshi, Y. S. Mayya, Arshad Khan, B. K. Sapra

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We have developed a CFD coupled aerosol microphysics model in the context of aerosol generation from a glowing wire. The governing equations can be solved implicitly for mass, momentum, energy transfer along with aerosol dynamics. The computationally efficient framework can simulate temporal behavior of total number concentration and number size distribution. This formulation uniquely couples standard K-Epsilon scheme with boundary layer model with detailed aerosol dynamics through residence time. This model uses measured temperatures (wire surface and axial/radial surroundings) and wire compositional data apart from other usual inputs for simulations. The model predictions show that bulk fluid motion and local heat distribution can significantly affect the aerosol behavior when the buoyancy effect in momentum transfer is considered. Buoyancy generated turbulence was found to be affecting parameters related to aerosol dynamics and transport as well. The model was validated by comparing simulated predictions with results obtained from six controlled experiments performed with a laboratory-made hot wire nanoparticle generator. Condensation particle counter (CPC) and scanning mobility particle sizer (SMPS) were used for measurement of total number concentration and number size distribution at the outlet of reactor cell during these experiments. Our model-predicted results were found to be in reasonable agreement with observed values. The developed model is fast (fully implicit) and numerically stable. It can be used specifically for applications in the context of the behavior of aerosol particles generated from glowing wire technique and in general for other similar large scale domains. Incorporation of CFD in aerosol microphysics framework provides a realistic platform to study natural convection driven systems/ applications. Aerosol dynamics sub-modules (nucleation, coagulation, wall deposition) have been coupled with Navier Stokes equations modified to include buoyancy coupled K-Epsilon turbulence model. Coupled flow-aerosol dynamics equation was solved numerically and in the implicit scheme. Wire composition and temperature (wire surface and cell domain) were obtained/measured, to be used as input for the model simulations. Model simulations showed a significant effect of fluid properties on the dynamics of aerosol particles. The role of buoyancy was highlighted by observation and interpretation of nucleation zones in the planes above the wire axis. The model was validated against measured temporal evolution, total number concentration and size distribution at the outlet of hot wire generator cell. Experimentally averaged and simulated total number concentrations were found to match closely, barring values at initial times. Steady-state number size distribution matched very well for sub 10 nm particle diameters while reasonable differences were noticed for higher size ranges. Although tuned specifically for the present context (i.e., aerosol generation from hotwire generator), the model can also be used for diverse applications, e.g., emission of particles from hot zones (chimneys, exhaust), fires and atmospheric cloud dynamics.

Keywords: nanoparticles, k-epsilon model, buoyancy, CFD, hot wire generator, aerosol dynamics

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Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: Rui Pedro de Sousa Guimarães Ferreira, Carlos Alberto Maia Domínguez

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Despite the ambitions to achieve climate neutrality by 2050, to fulfill the Paris Agreement's goals, the building and construction sector remains one of the most resource-intensive and greenhouse gas-emitting industries in the world, accounting for 40% of worldwide CO ₂ emissions. Over the past few decades, globalization and population growth have led to an exponential rise in demand in the housing market and, by extension, in the building industry. Considering this housing crisis, it is obvious that we will not stop building in the near future. However, the transition, which has already started, is challenging and complex because it calls for the worldwide participation of numerous organizations in altering how building systems, which have been a part of our everyday existence for over a century, are used. Wood is one of the alternatives that is most frequently used nowadays (under responsible forestry conditions) because of its physical qualities and, most importantly, because it produces fewer carbon emissions during manufacturing than steel or concrete. Furthermore, as wood retains its capacity to store CO ₂ after application and throughout the life of the building, working as a natural carbon filter, it helps to reduce greenhouse gas emissions. After a century-long focus on other materials, in the last few decades, technological advancements have made it possible to innovate systems centered around the use of wood. However, there are still some questions that require further exploration. It is necessary to standardize production and manufacturing processes based on prefabrication and modularization principles to achieve greater precision and optimization of the solutions, decreasing building time, prices, and waste from raw materials. In addition, this approach will make it possible to develop new architectural solutions to solve the rigidity and irreversibility of buildings, two of the most important issues facing housing today. Most current models are still created as inflexible, fixed, monofunctional structures that discourage any kind of regeneration, based on matrices that sustain the conventional family's traditional model and are founded on rigid, impenetrable compartmentalization. Adaptability and flexibility in housing are, and always have been, necessities and key components of architecture. People today need to constantly adapt to their surroundings and themselves because of the fast-paced, disposable, and quickly obsolescent nature of modern items. Migrations on a global scale, different kinds of co-housing, or even personal changes are some of the new questions that buildings have to answer. Designing with the reversibility of construction systems and materials in mind not only allows for the concept of "looping" in construction, with environmental advantages that enable the development of a circular economy in the sector but also unleashes multiple social benefits. In this sense, it is imperative to develop prefabricated and modular construction systems able to address the formalization of a reversible proposition that adjusts to the scale of time and its multiple reformulations, many of which are unpredictable. We must allow buildings to change, grow, or shrink over their lifetime, respecting their nature and, finally, the nature of the people living in them. It´s the ability to anticipate the unexpected, adapt to social factors, and take account of demographic shifts in society to stabilize communities, the foundation of real innovative sustainability.

Keywords: modular, timber, flexibility, housing

Procedia PDF Downloads 34

Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

Procedia PDF Downloads 49

Authors: Marian Mihalik, Kornel Csach, Martin Kovalik, Matúš Mihalik, Martina Kubovčíková, Maria Zentková, Martin Vavra, Vladimír Girman, Jaroslav Briančin, Marija Perovic, Marija Boškovic, Magdalena Fitta, Robert Pelka

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Current nanomaterials for use in biomedicine are based mainly on iron oxides and on present knowledge on magnetic nanostructures. Manganites can represent another material which can be used optionally. Manganites and their unique electronic properties have been extensively studied in the last decades not only due to fundamental interest but to possible applications of colossal magnetoresistance, magnetocaloric effect, and ferroelectric properties. It was found that the oxygen-reduction reaction on perovskite oxide is intimately connected with metal ion e.g., orbital occupation. The effect of oxygen deviation from the stoichiometric composition on crystal structure was studied very carefully by many authors on LaMnO₃. Depending on oxygen content, the crystal structure changes from orthorhombic one to rhombohedric for oxygen content 3.1. In the case of hole-doped manganites, the change from the orthorhombic crystal structure, which is typical for La1-xCaxMnO3 based manganites, to the rhombohedric crystal structure (La1-xMxMnO₃ where M = K, Ag, and Sr based materials) results in an enormous increase of the Curie temperature. In our paper, we study the effect of oxygen content on crystal structure, thermal, and magnetic properties (including magnetocaloric effect) of La1-xAgxMnO₃nano particle system. The content of oxygen in samples was tuned by heat treatment in different thermal regimes and in various environment (air, oxygen, argon). Water nanosuspensions based on La0.80Ag0.15MnO₃ magnetic particles with the Curie temperature of about 43oC were prepared by two different approaches. First, by using a laboratory circulation mill for milling of powder in the presence of sodium dodecyl sulphate (SDS) and subsequent centrifugation. Second nanosuspension was prepared using an agate bowl, etching in citric acid and HNO3, ultrasound homogeniser, centrifugation, and dextran 40 kDA or 15 kDA as surfactant. Electrostatic stabilisation obtained by the first approach did not offer long term kinetic and aggregation colloidal stability and was unable to compensate for attractive forces between particles under a magnetic field. By the second approach, we prepared suspension oversaturated by dextran 40 kDA for steric stabilisation, with evidence of the presence of superparamagnetic behaviour. Low concentration of nanoparticles and not ideal coverage of nanoparticles impacting the stability of ferrofluids was the disadvantage of this approach. Strong steric stabilisation was observable at alcaic conditions under pH = ~10. Application of dextran 15 kDA leads to relatively stable ferrofluid with pH around physiological conditions, but desegregation of powder by HNO₃ was not effective enough, and the average size of fragments was to large of about 150 nm, and we did not see any signature of superparamagnetic behaviour. The prepared ferrofluids were characterised by scanning and transition microscope method, thermogravimetry, magnetization, and AC susceptibility measurements. Specific Absorption Rate measurements were undertaken on powder as well on ferrofluids in order to estimate the potential application of La₀.₈₀Ag₀.₁₅MnO₃ magnetic particles based ferrofluid for hyperthermia. Our complex study contains an investigation of biocompatibility and potential biohazard of this material.

Keywords: manganites, magnetic nanoparticles, oxygen content, magnetic phase transition, magnetocaloric effect, ferrofluid, hyperthermia

Procedia PDF Downloads 64

Authors: Domenico Palladino, Nicolandrea Calabrese, Francesca Caffari, Giulia Centi, Francesca Margiotta, Giovanni Murano, Laura Ronchetti, Paolo Signoretti, Lisa Volpe, Silvia Di Turi

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The aim to achieve a fully decarbonized building stock by 2050 stands as one of the most challenging issues within the spectrum of energy and climate objectives. Numerous strategies are imperative, particularly emphasizing the reduction and optimization of energy demand. Ensuring the high energy performance of buildings emerges as a top priority, with measures aimed at cutting energy consumptions. Concurrently, it is imperative to decrease greenhouse gas emissions by using renewable energy sources for the on-site energy production, thereby striving for an energy balance leading towards zero-emission buildings. Italy's predominant building stock comprises ancient buildings, many of which hold historical significance and are subject to stringent preservation and conservation regulations. Attaining high levels of energy efficiency and reducing CO2 emissions in such buildings poses a considerable challenge, given their unique characteristics and the imperative to adhere to principles of conservation and restoration. Additionally, conducting a meticulous analysis of these buildings' current state is crucial for accurately quantifying their energy performance and predicting the potential impacts of proposed renovation strategies on energy consumption reduction. Within this framework, the paper presents a pilot case in Rome, outlining a methodological approach for the renovation of historic buildings towards achieving Zero Emission Building (ZEB) objective. The building has a mixed function with offices, a conference hall, and an exposition area. The building envelope is made of historical and precious materials used as cladding which must be preserved. A thorough understanding of the building's current condition serves as a prerequisite for analyzing its energy performance. This involves conducting comprehensive archival research, undertaking on-site diagnostic examinations to characterize the building envelope and its systems, and evaluating actual energy usage data derived from energy bills. Energy simulations and audit are the first step in the analysis with the assessment of the energy performance of the actual current state. Subsequently, different renovation scenarios are proposed, encompassing advanced building techniques, to pinpoint the key actions necessary for improving mechanical systems, automation and control systems, and the integration of renewable energy production. These scenarios entail different levels of renovation, ranging from meeting minimum energy performance goals to achieving the highest possible energy efficiency level. The proposed interventions are meticulously analyzed and compared to ascertain the feasibility of attaining the Zero Emission Building objective. In conclusion, the paper provides valuable insights that can be extrapolated to inform a broader approach towards energy-efficient refurbishment of historical buildings that may have limited potential for renovation in their building envelopes. By adopting a methodical and nuanced approach, it is possible to reconcile the imperative of preserving cultural heritage with the pressing need to transition towards a sustainable, low-carbon future.

Keywords: energy conservation and transition, energy efficiency in historical buildings, buildings energy performance, energy retrofitting, zero emission buildings, energy simulation

Procedia PDF Downloads 25

Authors: F. Pedro, S. Dias, A. Tadeu, J. António, Ó. López, A. Coelho

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Railway transportation is considered the most economical and sustainable way to travel. However, future mobility brings important challenges to railway operators. The main target is to develop solutions that stimulate sustainable mobility. The research and innovation goals for this domain are efficient solutions, ensuring an increased level of safety and reliability, improved resource efficiency, high availability of the means (train), and satisfied passengers with the travel comfort level. These requirements are in line with the European Strategic Agenda for the 2020 rail sector, promoted by the European Rail Research Advisory Council (ERRAC). All these aspects involve redesigning current equipment and, in particular, the interior of the carriages. Recent studies have shown that two of the most important requirements for passengers are reasonable ticket prices and comfortable interiors. Passengers tend to use their travel time to rest or to work, so train interiors and their systems need to incorporate features that meet these requirements. Among the various systems that integrate train interiors, the flooring system is one of the systems with the greatest impact on passenger safety and comfort. It is also one of the systems that takes more time to install on the train, and which contributes seriously to the weight (mass) of all interior systems. Additionally, it presents a strong impact on manufacturing costs. The design of railway floor, in the development phase, is usually made relying on a design software that allows to draw and calculate several solutions in a short period of time. After obtaining the best solution, considering the goals previously defined, experimental data is always necessary and required. This experimental phase has such great significance, that its outcome can provoke the revision of the designed solution. This paper presents the methodology and some of the results of an experimental characterisation of composite panels for railway application. The mechanical tests were made for unaged specimens and for specimens that suffered some type of aging, i.e. heat, cold and humidity cycles or freezing/thawing cycles. These conditionings aim to simulate not only the time effect, but also the impact of severe environmental conditions. Both full solutions and separated components/materials were tested. For the full solution, (panel) these were: four-point bending tests, tensile shear strength, tensile strength perpendicular to the plane, determination of the spreading of water, and impact tests. For individual characterisation of the components, more specifically for the covering, the following tests were made: determination of the tensile stress-strain properties, determination of flexibility, determination of tear strength, peel test, tensile shear strength test, adhesion resistance test and dimensional stability. The main conclusions were that experimental characterisation brings a huge contribution to understand the behaviour of the materials both individually and assembled. This knowledge contributes to the increase the quality and improvements of premium solutions. This research work was framed within the POCI-01-0247-FEDER-003474 (coMMUTe) Project funded by Portugal 2020 through the COMPETE 2020.

Keywords: durability, experimental characterization, mechanical tests, railway flooring system

Procedia PDF Downloads 128

Authors: Antonella Falanga, Armando Cartenì

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"Big data" refers to extremely vast and complex sets of data, encompassing extraordinarily large and intricate datasets that require specific tools for meaningful analysis and processing. These datasets can stem from diverse origins like sensors, mobile devices, online transactions, social media platforms, and more. The utilization of big data is pivotal, offering the chance to leverage vast information for substantial advantages across diverse fields, thereby enhancing comprehension, decision-making, efficiency, and fostering innovation in various domains. Big data, distinguished by its remarkable attributes of enormous volume, high velocity, diverse variety, and significant value, represent a transformative force reshaping the industry worldwide. Their pervasive impact continues to unlock new possibilities, driving innovation and advancements in technology, decision-making processes, and societal progress in an increasingly data-centric world. The use of these technologies is becoming more widespread, facilitating and accelerating operations that were once much more complicated. In particular, big data impacts across multiple sectors such as business and commerce, healthcare and science, finance, education, geography, agriculture, media and entertainment and also mobility and logistics. Within the transportation sector, which is the focus of this study, big data applications encompass a wide variety, spanning across optimization in vehicle routing, real-time traffic management and monitoring, logistics efficiency, reduction of travel times and congestion, enhancement of the overall transportation systems, but also mitigation of pollutant emissions contributing to environmental sustainability. Meanwhile, in public administration and the development of smart cities, big data aids in improving public services, urban planning, and decision-making processes, leading to more efficient and sustainable urban environments. Access to vast data reservoirs enables deeper insights, revealing hidden patterns and facilitating more precise and timely decision-making. Additionally, advancements in cloud computing and artificial intelligence (AI) have further amplified the potential of big data, enabling more sophisticated and comprehensive analyses. Certainly, utilizing big data presents various advantages but also entails several challenges regarding data privacy and security, ensuring data quality, managing and storing large volumes of data effectively, integrating data from diverse sources, the need for specialized skills to interpret analysis results, ethical considerations in data use, and evaluating costs against benefits. Addressing these difficulties requires well-structured strategies and policies to balance the benefits of big data with privacy, security, and efficient data management concerns. Building upon these premises, the current research investigates the efficacy and influence of big data by conducting an overview of the primary and recent implementations of big data in transportation systems. Overall, this research allows us to conclude that big data better provide to enhance rational decision-making for mobility choices and is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, public transport, sustainable mobility, transport demand, transportation planning

Procedia PDF Downloads 34

Authors: Medan Isaeva, Anna Degtyareva

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Context: Biliary atresia is a common reason for liver transplants in children, and the Kasai procedure can potentially be successful in avoiding the need for transplantation. However, it is important to identify factors that influence surgical outcomes in order to optimize treatment and improve patient outcomes. Research aim: The aim of this study was to develop prognostic models to assess the outcomes of the Kasai procedure in children with biliary atresia. Methodology: This retrospective study analyzed data from 166 children with biliary atresia who underwent the Kasai procedure between 2002 and 2021. The effectiveness of the operation was assessed based on specific criteria, including post-operative stool color, jaundice reduction, and bilirubin levels. The study involved a comparative analysis of various parameters, such as gestational age, birth weight, age at operation, physical development, liver and spleen sizes, and laboratory values including bilirubin, ALT, AST, and others, measured pre- and post-operation. Ultrasonographic evaluations were also conducted pre-operation, assessing the hepatobiliary system and related quantitative parameters. The study was carried out by two experienced specialists in pediatric hepatology. Comparative analysis and multifactorial logistic regression were used as the primary statistical methods. Findings: The study identified several statistically significant predictors of a successful Kasai procedure, including the presence of the gallbladder and levels of cholesterol and direct bilirubin post-operation. A detectable gallbladder was associated with a higher probability of surgical success, while elevated post-operative cholesterol and direct bilirubin levels were indicative of a reduced chance of positive outcomes. Theoretical importance: The findings of this study contribute to the optimization of treatment strategies for children with biliary atresia undergoing the Kasai procedure. By identifying early predictive signs of success, clinicians can modify treatment plans and manage patient care more effectively and proactively. Data collection and analysis procedures: Data for this analysis were obtained from the health records of patients who received the Kasai procedure. Comparative analysis and multifactorial logistic regression were employed to analyze the data and identify significant predictors. Question addressed: The study addressed the question of identifying predictive factors for the success of the Kasai procedure in children with biliary atresia. Conclusion: The developed prognostic models serve as valuable tools for early detection of patients who are less likely to benefit from the Kasai procedure. This enables clinicians to modify treatment plans and manage patient care more effectively and proactively. Potential limitations of the study: The study has several limitations. Its retrospective nature may introduce biases and inconsistencies in data collection. Being single centered, the results might not be generalizable to wider populations due to variations in surgical and postoperative practices. Also, other potential influencing factors beyond the clinical, laboratory, and ultrasonographic parameters considered in this study were not explored, which could affect the outcomes of the Kasai operation. Future studies could benefit from including a broader range of factors.

Keywords: biliary atresia, kasai operation, prognostic model, native liver survival

Procedia PDF Downloads 27

Authors: Andreia Garrido, Artur Conde, Ana Cunha, Ric De Vos

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Climate changes predictions point to increases in abiotic stress for crop plants in Portugal, like pronounced temperature variation and decreased precipitation, which will have negative impact on grapevine physiology and consequently, on grape berry and wine quality. Short-term mitigation strategies have, therefore, been implemented to alleviate the impacts caused by adverse climatic periods. These strategies include foliar application of kaolin, an inert mineral, which has radiation reflection proprieties that decreases stress from excessive heat/radiation absorbed by its leaves, as well as smart irrigation strategies to avoid water stress. However, little is known about the influence of these mitigation measures on grape berries, neither on the photosynthetic activity nor on the photosynthesis-related metabolic profiles of its various tissues. Moreover, the role of fruit photosynthesis on berry quality is poorly understood. The main objective of our work was to assess the effects of kaolin and irrigation treatments on the photosynthetic activity of grape berry tissues (exocarp and seeds) and on their global metabolic profile, also investigating their possible relationship. We therefore collected berries of field-grown plants of the white grape variety Alvarinho from two distinct microclimates, i.e. from clusters exposed to high light (HL, 150 µmol photons m⁻² s⁻¹) and low light (LL, 50 µmol photons m⁻² s⁻¹), from both kaolin and non-kaolin (control) treated plants at three fruit developmental stages (green, véraison and mature). Plant irrigation was applied after harvesting the green berries, which also enabled comparison of véraison and mature berries from irrigated and non-irrigated growth conditions. Photosynthesis was assessed by pulse amplitude modulated chlorophyll fluorescence imaging analysis, and the metabolite profile of both tissues was assessed by complementary metabolomics approaches. Foliar kaolin application resulted in, for instance, an increased photosynthetic activity of the exocarp of LL-grown berries at green developmental stage, as compared to the control non-kaolin treatment, with a concomitant increase in the levels of several lipid-soluble isoprenoids (chlorophylls, carotenoids, and tocopherols). The exocarp of mature berries grown at HL microclimate on kaolin-sprayed non-irrigated plants had higher total sugar levels content than all other treatments, suggesting that foliar application of this mineral results in an increased accumulation of photoassimilates in mature berries. Unbiased liquid chromatography-mass spectrometry-based profiling of semi-polar compounds followed by ASCA (ANOVA simultaneous component analysis) and ANOVA statistical analysis indicated that kaolin had no or inconsistent effect on the flavonoid and phenylpropanoid composition in both seed and exocarp at any developmental stage; in contrast, both microclimate and irrigation influenced the level of several of these compounds depending on berry ripening stage. Overall, our study provides more insight into the effects of mitigation strategies on berry tissue photosynthesis and phytochemistry, under contrasting conditions of cluster light microclimate. We hope that this may contribute to develop sustainable management in vineyards and to maintain grape berries and wines with high quality even at increasing abiotic stress challenges.

Keywords: climate change, grape berry tissues, metabolomics, mitigation strategies

Procedia PDF Downloads 92

Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservice architectures are increasingly in distributed cloud applications due to the advantages on the software composition, development speed, release cycle frequency and the business logic time to market. On the other hand, these architectures also introduce some challenges on the testing and release phases of applications. Container technology solves some of these issues by providing reproducible environments, easy of software distribution and isolation of processes. However, there are other issues that remain unsolved in current container technology when dealing with multiple machines, such as networking for multi-host communication, service discovery, load balancing or data persistency (even though some of these challenges are already solved by traditional cloud vendors in a very mature and widespread manner). Container cluster management tools, such as Kubernetes, Mesos or Docker Swarm, attempt to solve these problems by introducing a new control layer where the unit of deployment is the container (or the pod — a set of strongly related containers that must be deployed on the same machine). These tools are complex to configure and manage and they do not follow a pure immutable infrastructure approach since servers are reused between deployments. Indeed, these tools introduce dependencies at execution time for solving networking or service discovery problems. If an error on the control layer occurs, which would affect running applications, specific expertise is required to perform ad-hoc troubleshooting. As a consequence, it is not surprising that container cluster support is becoming a source of revenue for consulting services. This paper presents i2kit, a deployment tool based on the immutable infrastructure pattern, where the virtual machine is the unit of deployment. The input for i2kit is a declarative definition of a set of microservices, where each microservice is defined as a pod of containers. Microservices are built into machine images using linuxkit —- a tool for creating minimal linux distributions specialized in running containers. These machine images are then deployed to one or more virtual machines, which are exposed through a cloud vendor load balancer. Finally, the load balancer endpoint is set into other microservices using an environment variable, providing service discovery. The toolkit i2kit reuses the best ideas from container technology to solve problems like reproducible environments, process isolation, and software distribution, and at the same time relies on mature, proven cloud vendor technology for networking, load balancing and persistency. The result is a more robust system with no learning curve for troubleshooting running applications. We have implemented an open source prototype that transforms i2kit definitions into AWS cloud formation templates, where each microservice AMI (Amazon Machine Image) is created on the fly using linuxkit. Even though container cluster management tools have more flexibility for resource allocation optimization, we defend that adding a new control layer implies more important disadvantages. Resource allocation is greatly improved by using linuxkit, which introduces a very small footprint (around 35MB). Also, the system is more secure since linuxkit installs the minimum set of dependencies to run containers. The toolkit i2kit is currently under development at the IMDEA Software Institute.

Keywords: container, deployment, immutable infrastructure, microservice

Procedia PDF Downloads 153

Authors: Veenu Bala, Yashpal S. Chhonker, Bhavana Kushwaha, Rabi S. Bhatta, Gopal Gupta, Vishnu L. Sharma

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According to UNAIDS 2013 estimate nearly 52% of all individuals living with HIV are now women of reproductive age (15–44 years). Seventy-five percent cases of HIV acquisition are through heterosexual contacts and sexually transmitted infections (STIs), attributable to unsafe sexual behaviour. Each year, an estimated 500 million people acquire atleast one of four STIs: chlamydia, gonorrhoea, syphilis and trichomoniasis. Trichomonas vaginalis (TV) is exclusively sexually transmitted in adults, accounting for 30% of STI cases and associated with pelvic inflammatory disease (PID), vaginitis and pregnancy complications in women. TV infection resulted in impaired vaginal milieu, eventually favoring HIV transmission. In the absence of an effective prophylactic HIV vaccine, prevention of new infections has become a priority. It was thought worthwhile to integrate HIV prevention and reproductive health services including unintended pregnancy protection for women as both are related with unprotected sex. Initially, nonoxynol-9 (N-9) had been proposed as a spermicidal agent with microbicidal activity but on the contrary it increased HIV susceptibility due to surfactant action. Thus, to accomplish an urgent need of novel woman controlled non-detergent microbicidal spermicides benzenepropanamine analogues have been synthesized. At first, five benzenepropanamine-dithiocarbamate hybrids have been synthesized and evaluated for their spermicidal, anti-Trichomonas and anti-fungal activities along with safety profiling to cervicovaginal cells. In order to further enhance the scope of above study benzenepropanamine was hybridized with thiourea as to introduce anti-HIV potential. The synthesized hybrid molecules were evaluated for their reverse transcriptase (RT) inhibition, spermicidal, anti-Trichomonas and antimicrobial activities as well as their safety against vaginal flora and cervical cells. simulated vaginal fluid (SVF) stability and pharmacokinetics of most potent compound versus N-9 was examined in female Newzealand (NZ) rabbits to observe its absorption into systemic circulation and subsequent exposure in blood plasma through vaginal wall. The study resulted in the most promising compound N-butyl-4-(3-oxo-3-phenylpropyl) piperazin-1-carbothioamide (29) exhibiting better activity profile than N-9 as it showed RT inhibition (72.30 %), anti-Trichomonas (MIC, 46.72 µM against MTZ susceptible and MIC, 187.68 µM against resistant strain), spermicidal (MEC, 0.01%) and antifungal activity (MIC, 3.12–50 µg/mL) against four fungal strains. The high safety against vaginal epithelium (HeLa cells) and compatibility with vaginal flora (lactobacillus), SVF stability and least vaginal absorption supported its suitability for topical vaginal application. Docking study was performed to gain an insight into the binding mode and interactions of the most promising compound, N-butyl-4-(3-oxo-3-phenylpropyl) piperazin-1-carbothioamide (29) with HIV-1 Reverse Transcriptase. The docking study has revealed that compound (29) interacted with HIV-1 RT similar to standard drug Nevirapine. It may be concluded that hybridization of benzenepropanamine and thiourea moiety resulted into novel lead with multiple activities including RT inhibition. A further lead optimization may result into effective vaginal microbicides having spermicidal, anti-Trichomonas, antifungal and anti-HIV potential altogether with enhanced safety to cervico-vaginal cells in comparison to Nonoxynol-9.

Keywords: microbicidal, nonoxynol-9, reverse transcriptase, spermicide

Procedia PDF Downloads 325

Authors: K. Karapetyan, F. Tkhruni, A. Aghajanyan, T. S. Balabekyan, L. Arstamyan

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Introduction: Globalization of the food supply has created the conditions favorable for the emergence and spread of food-borne and especially dangerous pathogens (EDP) in developing countries. The fresh-cut fruit and vegetable industry is searching for alternatives to replace chemical treatments with biopreservative approaches that ensure the safety of the processed foods product. Antimicrobial compounds of lactic acid bacteria (LAB) possess bactericidal or bacteriostatic activity against intestinal pathogens, spoilage organisms and food-borne pathogens such as Listeria monocytogenes, Staphylococcus aureus and Salmonella. Endemic strains of LAB were isolated. The strains, showing broad spectrum of antimicrobial activity against food spoiling microorganisms, were selected. The genotyping by 16S rRNA sequencing, GS-PCR, RAPD PCR methods showed that they were presented by Lactobacillus rhamnosus109, L.plantarum 65, L.plantarum 66 and Enterococcus faecium 64 species. LAB are deposited in "Microbial Depository Center" (MDC) SPC "Armbiotechnology". Methods: LAB strains were isolated from different dairy products from rural households from the highland regions of Armenia. Serially diluted samples were spread on MRS (Merck, Germany) and hydrolyzed milk agar (1,2 % w/v). Single colonies from each LAB were individually inoculated in liquid MRS medium and incubated at 37oC for 24 hours. Culture broth with biomass was centrifuged at 10,000 g during 20 min for obtaining of cell free culture broth (CFC). The antimicrobial substances from CFC broth were purified by the combination of adsorption-desorption and ion-exchange chromatography methods. Separation of bacteriocins was performed using a HPLC method on "Avex ODS" C18 column. Mass analysis of peptides recorded on the device API 4000 in the electron ionization mode. The spot-on-lawn method on the test culture plated in the solid medium was applied. The antimicrobial activity is expressed in arbitrary units (AU/ml). Results. Purification of CFC broth of LAB allowed to obtain partially purified antimicrobial preparations which contains bacteriocins with broad spectrum of antimicrobial activity. Investigation of their main biochemical properties shown, that inhibitory activity of preparations is partially reduced after treatment with proteinase K, trypsin, pepsin, suggesting a proteinaceous nature of bacteriocin-like substances containing in CFC broth. Preparations preserved their activity after heat treatment (50-121 oC, 20 min) and were stable in the pH range 3–8. The results of SDS PAAG electrophoresis show that L.plantarum 66 and Ent.faecium 64 strains have one bacteriocin (BCN) with maximal antimicrobial activity with approximate molecular weight 2.0-3.0 kDa. From L.rhamnosus 109 two BCNs were obtained. Mass spectral analysis indicates that these bacteriocins have peptide bonds and molecular weight of BCN 1 and BCN 2 are approximately 1.5 kDa and 700 Da. Discussion: Thus, our experimental data shown, that isolated endemic strains of LAB are able to produce bacteriocins with high and different inhibitory activity against broad spectrum of microorganisms of different taxonomic group, such as Salmonella sp., Esherichia coli, Bacillus sp., L.monocytogenes, Proteus mirabilis, Staph. aureus, Ps. aeruginosa. Obtained results proved the perspectives for use of endemic strains in the preservation of foodstuffs. Acknowledgments: This work was realized with financial support of the Project Global Initiatives for Preliferation Prevention (GIPP) T2- 298, ISTC A-1866.

Keywords: antimicrobial activity, bacteriocins, endemic strains, food safety

Procedia PDF Downloads 542

Authors: Omaima A. Sharaf, Wafaa M. Abd El-Rahim, Hassan Moawad, Michael J. Sadowsky

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Textile industry is one of the important industries in the worldwide. It is known that the eco-friendly industrial and agricultural activities are significant for socio-economic stability of all countries. The absence of appropriate industrial waste water treatments is essential barrier for sustainable development in food and agricultural sectors especially in developing country like Egypt. Thus, the development of enzymatic bioremediation technology for textile dye removal will enhance the collaboration between scientists who develop the technology and industry where this technology will be implemented towards the safe disposal of the textile dye wastes. Highly efficient microorganisms are of most importance in developing and using highly effective biological treatment processes. Bacterial degradation of azo dyes is generally initiated by an enzymatic step that involves cleavage of azo linkages, usually with the aid of an azoreductase as electron donor. Thus, expanding the spectrum of microorganisms with high enzymatic activities as azoreductases and discovering novel azo-dye degrading enzymes, with enhanced stability and superior catalytic properties, are necessary for many environmental and industrial applications. Consequently, the use of molecular tools has become increasingly integrated into the understanding of enzyme properties and characterization. Researchers have utilized a gene cloning and expression methods as a tool to produce recombinant protein for decolorizing dyes more efficiently. Thus, presumptive evidence for the presence of genes encoding azoreductases in the genomes of selected local, and most potent azo-degrading strains were obtained by using specific oligonucleotides primers. These potent strains have been isolated from textile industrial wastewater in Egypt and identified using 16S rRNA sequence analysis as 'Lysinibacillus macrolidesB8, Brevibacillus parabrevisB11, Bacillus coagulansB7, and B. cereusB5'. PCR products of two full length genes designated as (AZO1;621bp and AZO2;534bp) were detected. BLASTx results indicated that AZO1 gene was corresponding to predicted azoreductase from of Bacillus sp. ABP14, complete genome, multispecies azoreductase [Bacillus], It was submitted to the gene bank by an accession no., BankIt2085371 AZO1 MG923210 (621bp; 207 amino acids). AZO1 was generated from the DNA of our identified strains Lysinibacillus macrolidesB8. On the other hand, AZO2 gene was corresponding to a predicted azoreductase from Bacillus cereus strain S2-8. Gene bank accession no. was BankIt2085839 AZO2 MG932081 (534bp;178 amino acids) and it was amplified from our Bacillus coagulansB7. Both genes were successfully cloned into pCR2.1TOPO (Invitrogen) and in pET28b+ vectors, then they transformed into E. coli DH5α and BL21(DE3) cells for heterologous expression studies. Our recombinant azoreductases (AZO1&AZO2) exhibited potential enzyme activity and efficiently decolorized an azo dye (Direct violet). They exhibited pH stability between 6 and 8 with optimum temperature up to 60°C and 37 °C after induction by 1mM and 1.5mM IPTG, for both AZO1 &AZO2, respectively. These results suggested that further optimization and purification of these recombinant proteins by using different heterologous expression systems will give great potential for the sustainable utilization of these recombinant enzymes in several industrial applications especially in wastewater treatments.

Keywords: azoreductases, decolorization, enzyme activity, gene cloning and expression

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Authors: Salvatore Luongo, Carlo Luongo

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This paper discusses the implementation solutions to reduce the computational load for the Traffic Situational Awareness with Alerts (TSAA) application, based on Automatic Dependent Surveillance-Broadcast (ADS-B) technology. In 2008, there were 23 total mid-air collisions involving general aviation fixed-wing aircraft, 6 of which were fatal leading to 21 fatalities. These collisions occurred during visual meteorological conditions, indicating the limitations of the see-and-avoid concept for mid-air collision avoidance as defined in the Federal Aviation Administration’s (FAA). The commercial aviation aircraft are already equipped with collision avoidance system called TCAS, which is based on classic transponder technology. This system dramatically reduced the number of mid-air collisions involving air transport aircraft. In general aviation, the same reduction in mid-air collisions has not occurred, so this reduction is the main objective of the TSAA application. The major difference between the original conflict detection application and the TSAA application is that the conflict detection is focused on preventing loss of separation in en-route environments. Instead TSAA is devoted to reducing the probability of mid-air collision in all phases of flight. The TSAA application increases the flight crew traffic situation awareness providing alerts of traffic that are detected in conflict with ownship in support of the see-and-avoid responsibility. The relevant effort has been spent in the design process and the code generation in order to maximize the efficiency and performances in terms of computational load and memory consumption reduction. The TSAA architecture is divided into two high-level systems: the “Threats database” and the “Conflict detector”. The first one receives the traffic data from ADS-B device and provides the memorization of the target’s data history. Conflict detector module estimates ownship and targets trajectories in order to perform the detection of possible future loss of separation between ownship and each target. Finally, the alerts are verified by additional conflict verification logic, in order to prevent possible undesirable behaviors of the alert flag. In order to reduce the computational load, a pre-check evaluation module is used. This pre-check is only a computational optimization, so the performances of the conflict detector system are not modified in terms of number of alerts detected. The pre-check module uses analytical trajectories propagation for both target and ownship. This allows major accuracy and avoids the step-by-step propagation, which requests major computational load. Furthermore, the pre-check permits to exclude the target that is certainly not a threat, using an analytical and efficient geometrical approach, in order to decrease the computational load for the following modules. This software improvement is not suggested by FAA documents, and so it is the main innovation of this work. The efficiency and efficacy of this enhancement are verified using fast-time and real-time simulations and by the execution on a real device in several FAA scenarios. The final implementation also permits the FAA software certification in compliance with DO-178B standard. The computational load reduction allows the installation of TSAA application also on devices with multiple applications and/or low capacity in terms of available memory and computational capabilities

Keywords: traffic situation awareness, general aviation, aircraft conflict detection, computational load reduction, implementation solutions, software certification

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Authors: Vanja Vlajkov, Ivana PajčIn, Mila Grahovac, Marta Loc, Dragana Budakov, Jovana Grahovac

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The rhizosphere soil refers to the plant roots' dynamic environment characterized by their inhabitants' high biological activity. Rhizospheric bacteria are recognized as effective biocontrol agents and considered cardinal in alternative strategies for securing ecological plant diseases management. The need to suppress fungal pathogens is an urgent task, not only because of the direct economic losses caused by infection but also due to their ability to produce mycotoxins with harmful effects on human health. Aspergillus and Fusarium species are well-known producers of toxigenic metabolites with a high capacity to colonize crops and enter the food chain. The bacteria belonging to the Bacillus genus has been conceded as a plant beneficial species in agricultural practice and identified as plant growth-promoting rhizobacteria (PGPR). Besides incontestable potential, the full commercialization of microbial biopesticides is in the preliminary phase. Thus, there is a constant need for estimating the suitability of novel strains to be used as a central point of viable bioprocess leading to market-ready product development. In the present study, 76 potential producing strains were isolated from the rhizosphere soil, sampled from different localities in the Autonomous Province of Vojvodina, Republic of Serbia. The selective isolation process of strains started by resuspending 1 g of soil samples in 9 ml of saline and incubating at 28° C for 15 minutes at 150 rpm. After homogenization, thermal treatment at 100° C for 7 minutes was performed. Dilution series (10-1-10-3) were prepared, and 500 µl of each was inoculated on nutrient agar plates and incubated at 28° C for 48 h. The pure cultures of morphologically different strains indicating belonging to the Bacillus genus were obtained by the spread-plate technique. The cultivation of the isolated strains was carried out in an Erlenmeyer flask for 96 h, at 28 °C, 170 rpm. The antagonistic activity screening included two phytopathogenic fungi as test microorganisms: Aspergillus sp. and Fusarium sp. The mycelial growth inhibition was estimated based on the antimicrobial activity testing of cultivation broth by the diffusion method. For the Aspergillus sp., the highest antifungal activity was recorded for the isolates Kro-4a and Mah-1a. In contrast, for the Fusarium sp., following 15 isolates exhibited the highest antagonistic effect Par-1, Par-2, Par-3, Par-4, Kup-4, Paš-1b, Pap-3, Kro-2, Kro-3a, Kro-3b, Kra-1a, Kra-1b, Šar-1, Šar-2b and Šar-4. One-way ANOVA was performed to determine the antagonists' effect statistical significance on inhibition zone diameter. Duncan's multiple range test was conducted to define homogenous groups of antagonists with the same level of statistical significance regarding their effect on antimicrobial activity of the tested cultivation broth against tested pathogens. The study results have pointed out the significant in vitro potential of the isolated strains to be used as biocontrol agents for the suppression of the tested mycotoxigenic fungi. Further research should include the identification and detailed characterization of the most promising isolates and mode of action of the selected strains as biocontrol agents. The following research should also involve bioprocess optimization steps to fully reach the selected strains' potential as microbial biopesticides and design cost-effective biotechnological production.

Keywords: Bacillus, biocontrol, bioprocess, mycotoxigenic fungi

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Authors: D. Malouch, M. Berchel, C. Dreanno, S. Stachowski-Haberkorn, P-A. Jaffres

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Biofilm is a predominant lifestyle chosen by bacteria. Whether it is developed on an immerged surface or a mobile biofilm known as flocs, the bacteria within this form of life show properties different from its planktonic ones. Within the biofilm, the self-formed matrix of Extracellular Polymeric Substances (EPS) offers hydration, resources capture, enhanced resistance to antimicrobial agents, and allows cell-communication. Biofouling is a complex natural phenomenon that involves biological, physical and chemical properties related to the environment, the submerged surface and the living organisms involved. Bio-colonization of artificial structures can cause various economic and environmental impacts. The increase in costs associated with the over-consumption of fuel from biocolonized vessels has been widely studied. Measurement drifts from submerged sensors, as well as obstructions in heat exchangers, and deterioration of offshore structures are major difficulties that industries are dealing with. Therefore, surfaces that inhibit biocolonization are required in different areas (water treatment, marine paints, etc.) and many efforts have been devoted to produce efficient and eco-compatible antifouling agents. The different steps of surface fouling are widely described in literature. Studying the biofilm and its stages provides a better understanding of how to elaborate more efficient antifouling strategies. Several approaches are currently applied, such as the use of biocide anti-fouling paint6 (mainly with copper derivatives) and super-hydrophobic coatings. While these two processes are proving to be the most effective, they are not entirely satisfactory, especially in a context of a changing legislation. Nowadays, the challenge is to prevent biofouling with non-biocide compounds, offering a cost effective solution, but with no toxic effects on marine organisms. Since the micro-fouling phase plays an important role in the regulation of the following steps of biofilm formation7, it is desired to reduce or delate biofouling of a given surface by inhibiting the micro fouling at its early stages. In our recent works, we reported that some amphiphilic compounds exhibited bacteriostatic or bactericidal properties at a concentration that did not affect eukaryotic cells. These remarkable properties invited us to assess this type of bio-inspired phospholipids9 to prevent the colonization of surfaces by marine bacteria. Of note, other studies reported that amphiphilic compounds interacted with bacteria leading to a reduction of their development. An amphiphilic compound is a molecule consisting of a hydrophobic domain and a polar head (ionic or non-ionic). These compounds appear to have interesting antifouling properties: some ionic compounds have shown antimicrobial activity, and zwitterions can reduce nonspecific adsorption of proteins. Herein, we investigate the potential of amphiphilic compounds as inhibitors of bacterial growth and marine biofilm formation. The aim of this study is to compare the efficacy of four synthetic phospholipids that features a cationic charge (BSV36, KLN47) or a zwitterionic polar-head group (SL386, MB2871) to prevent microfouling with marine bacteria. We also study the toxicity of these compounds in order to identify the most promising compound that must feature high anti-adhesive properties and a low cytotoxicity on two links representative of coastal marine food webs: phytoplankton and oyster larvae.

Keywords: amphiphilic phospholipids, bacterial biofilm, marine microfouling, non-toxic antifouling

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Authors: Ankur Chaudhuri, Sibani Sen Chakraborty

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In human, glutaminyl cyclase activity is highly abundant in neuronal and secretory tissues and is preferentially restricted to hypothalamus and pituitary. The N-terminal modification of β-amyloids (Aβs) peptides by the generation of a pyro-glutamyl (pGlu) modified Aβs (pE-Aβs) is an important process in the initiation of the formation of neurotoxic plaques in Alzheimer’s disease (AD). This process is catalyzed by glutaminyl cyclase (QC). The expression of QC is characteristically up-regulated in the early stage of AD, and the hallmark of the inhibition of QC is the prevention of the formation of pE-Aβs and plaques. A computer-aided drug design (CADD) process was employed to give an idea for the designing of potentially active compounds to understand the inhibitory potency against human glutaminyl cyclase (QC). This work elaborates the ligand-based and structure-based pharmacophore exploration of glutaminyl cyclase (QC) by using the known inhibitors. Three dimensional (3D) quantitative structure-activity relationship (QSAR) methods were applied to 154 compounds with known IC50 values. All the inhibitors were divided into two sets, training-set, and test-sets. Generally, training-set was used to build the quantitative pharmacophore model based on the principle of structural diversity, whereas the test-set was employed to evaluate the predictive ability of the pharmacophore hypotheses. A chemical feature-based pharmacophore model was generated from the known 92 training-set compounds by HypoGen module implemented in Discovery Studio 2017 R2 software package. The best hypothesis was selected (Hypo1) based upon the highest correlation coefficient (0.8906), lowest total cost (463.72), and the lowest root mean square deviation (2.24Å) values. The highest correlation coefficient value indicates greater predictive activity of the hypothesis, whereas the lower root mean square deviation signifies a small deviation of experimental activity from the predicted one. The best pharmacophore model (Hypo1) of the candidate inhibitors predicted comprised four features: two hydrogen bond acceptor, one hydrogen bond donor, and one hydrophobic feature. The Hypo1 was validated by several parameters such as test set activity prediction, cost analysis, Fischer's randomization test, leave-one-out method, and heat map of ligand profiler. The predicted features were then used for virtual screening of potential compounds from NCI, ASINEX, Maybridge and Chembridge databases. More than seven million compounds were used for this purpose. The hit compounds were filtered by drug-likeness and pharmacokinetics properties. The selective hits were docked to the high-resolution three-dimensional structure of the target protein glutaminyl cyclase (PDB ID: 2AFU/2AFW) to filter these hits further. To validate the molecular docking results, the most active compound from the dataset was selected as a reference molecule. From the density functional theory (DFT) study, ten molecules were selected based on their highest HOMO (highest occupied molecular orbitals) energy and the lowest bandgap values. Molecular dynamics simulations with explicit solvation systems of the final ten hit compounds revealed that a large number of non-covalent interactions were formed with the binding site of the human glutaminyl cyclase. It was suggested that the hit compounds reported in this study could help in future designing of potent inhibitors as leads against human glutaminyl cyclase.

Keywords: glutaminyl cyclase, hit lead, pharmacophore model, simulation

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Authors: M. Shahab Uddin, Pennung Warnitchai

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Currently more than half of the world’s populations are living in cities, and the number and sizes of cities are growing faster than ever. Cities rely on the effective functioning of complex and interdependent critical infrastructures networks to provide public services, enhance the quality of life, and save the community from hazards and disasters. In contrast, complex connectivity and interdependency among the urban critical infrastructures bring management challenges and make the urban system prone to the domino effect. Unplanned rapid growth, increased connectivity, and interdependency among the infrastructures, resource scarcity, and many other socio-political factors are affecting the typical state of an urban system and making it susceptible to numerous sorts of diversion. In addition to internal vulnerabilities, urban systems are consistently facing external threats from natural and manmade hazards. Cities are not just complex, interdependent system, but also makeup hubs of the economy, politics, culture, education, etc. For survival and sustainability, complex urban systems in the current world need to manage their vulnerabilities and hazardous incidents more wisely and more interactively. Coordinated management in such systems makes for huge potential when it comes to absorbing negative effects in case some of its components were to function improperly. On the other hand, ineffective management during a similar situation of overall disorder from hazards devastation may make the system more fragile and push the system to an ultimate collapse. Following the quantum, the current research hypothesizes that a hazardous event starts its journey as an emergency, and the system’s internal vulnerability and response capacity determine its destination. Connectivity and interdependency among the urban critical infrastructures during this stage may transform its vulnerabilities into dynamic damaging force. An emergency may turn into a disaster in the absence of effective management; similarly, mismanagement or lack of management may lead the situation towards a catastrophe. Situation awareness and factual decision-making is the key to win a battle. The current research proposed a contextual decision support system for an urban critical infrastructure system while integrating three different models: 1) Damage cascade model which demonstrates damage propagation among the infrastructures through their connectivity and interdependency, 2) Restoration model, a dynamic restoration process of individual infrastructure, which is based on facility damage state and overall disruptions in surrounding support environment, and 3) Optimization model that ensures optimized utilization and distribution of available resources in and among the facilities. All three models are tightly connected, mutually interdependent, and together can assess the situation and forecast the dynamic outputs of every input. Moreover, this integrated model will hold disaster managers and decision makers responsible when it comes to checking all the alternative decision before any implementation, and support to produce maximum possible outputs from the available limited inputs. This proposed model will not only support to reduce the extent of damage cascade but will ensure priority restoration and optimize resource utilization through adaptive and collaborative management. Complex systems predictably fail but in unpredictable ways. System understanding, situation awareness, and factual decisions may significantly help urban system to survive and sustain.

Keywords: disaster prevention, decision support system, emergency response, urban critical infrastructure system

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Authors: D. Bianco, A. Sollazzo, M. Barbarino, G. Elia, A. Smoraldi, N. Favaloro

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The activities, described in the present paper, have been conducted in the framework of the HYPROB-New Program, carried out by the Italian Aerospace Research Centre (CIRA) promoted and funded by the Italian Ministry of University and Research (MIUR) in order to improve the National background on rocket engine systems for space applications. The Program has the strategic objective to improve National system and technology capabilities in the field of liquid rocket engines (LRE) for future Space Propulsion Systems applications, with specific regard to LOX/LCH4 technology. The main purpose of the HYPROB program is to design and build a Propulsion Test Facility (HIMP) allowing test activities on Liquid Thrusters. The development of skills in liquid rocket propulsion can only pass through extensive test campaign. Following its mission, CIRA has planned the development of new testing facilities and infrastructures for space propulsion characterized by adequate sizes and instrumentation. The IMP test cell is devoted to testing articles representative of small combustion chambers, fed with oxygen and methane, both in liquid and gaseous phase. This article describes the activities that have been carried out for the evaluation of the acoustic impact, and its consequent mitigation. The impact of the simulated acoustic disturbance has been evaluated, first, using an approximated method based on experimental data by Baumann and Coney, included in “Noise and Vibration Control Engineering” edited by Vér and Beranek. This methodology, used to evaluate the free-field radiation of jet in ideal acoustical medium, analyzes in details the jet noise and assumes sources acting at the same time. It considers as principal radiation sources the jet mixing noise, caused by the turbulent mixing of jet gas and the ambient medium. Empirical models, allowing a direct calculation of the Sound Pressure Level, are commonly used for rocket noise simulation. The model named after K. Eldred is probably one of the most exploited in this area. In this paper, an improvement of the Eldred Standard model has been used for a detailed investigation of the acoustical impact of the Hyprob facility. This new formulation contains an explicit expression for the acoustic pressure of each equivalent noise source, in terms of amplitude and phase, allowing the investigation of the sources correlation effects and their propagation through wave equations. In order to enhance the evaluation of the facility acoustic impact, including an assessment of the mitigation strategies to be set in place, a more advanced simulation campaign has been conducted using both an in-house code for noise propagation and scattering, and a commercial code for industrial noise environmental impact, CadnaA. The noise prediction obtained with the revised Eldred-based model has then been used for formulating an empirical/BEM (Boundary Element Method) hybrid approach allowing the evaluation of the barrier mitigation effect, at the design. This approach has been compared with the analogous empirical/ray-acoustics approach, implemented within CadnaA using a customized definition of sources and directivity factor. The resulting impact evaluation study is reported here, along with the design-level barrier optimization for noise mitigation.

Keywords: acoustic impact, industrial noise, mitigation, rocket noise

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